Does hedging affect firm value? Evidence from the US airline industry

Financial Management (Financial Management Association), Spring, 2006 by David A. Carter, Daniel A. Rogers, Betty J. Simkins

Within the industry, some airlines use avenues other than hedging future fuel purchases to manage fuel price risk. For example, some smaller carriers contract with major airlines to provide service to smaller communities near the major airline's hub. These carriers may have a fuel pass-through agreement where the major carrier absorbs the risk of fluctuating fuel prices. Table I indicates if carriers disclose such fuel pass-through agreements. Similar to fuel pass-through agreements, charter airlines typically do not bear the risk of fluctuating fuel prices. The charter's customer reimburses fuel costs. The final column of Table I indicates airlines classified as having charter operations. (7) One point worth noting about fuel pass-through and charter agreements is that these mechanisms do not lock in a price (or price cap) for future jet fuel, as is the case when airlines hedge future fuel purchases. Rather, users of these mechanisms experience higher fuel costs as fuel prices increase, but allow airlines to pass the higher fuel cost to another party (i.e., the partner airline or the chartering customer). If the demand for air travel is price-elastic, then fuel pass-through and chartering arrangements are not equivalent to hedging future fuel purchases. The former two mechanisms will be associated with lower passenger demand if fuel prices rise, while the latter strategy allows airlines to maintain current fares in spite of higher fuel prices. In subsequent analyses, we differentiate fuel hedging from these other fuel risk management mechanisms.

Thus far, we have discussed the fact that airlines appear to view volatile jet fuel prices as a source of risk exposure. Next, we explore two possible ways of measuring airline exposure to jet fuel prices. First, we estimate a monthly market model using an equally-weighted airline industry return that includes a jet fuel return factor. This type of methodology is standard in other research examining risk exposures. (8) We conduct the following monthly time-series regression:

[R.sub.t] = [alpha] [beta][R.sub.mt] [gamma][R.sub.Jt] [e.sub.t], (1)

where [R.sub.t] is the equally-weighted rate of return on the sample airlines in month t (as gathered from CRSP), [R.sub.mt] is the return on the CRSP equally-weighted market portfolio, [R.sub.Jt], is the percentage change in Gulf Coast spot jet fuel prices (gathered from the Energy Information Administration), and [[epsilon].sub.t] is the idiosyncratic error term. (9) The estimated coefficient, [gamma], is a measure of the sensitivity of the industry's stock price to changes in jet fuel prices. We expect airlines to be negatively exposed to the price of jet fuel.

In untabulated results, we find that airline industry stock prices are negatively related to jet fuel prices. The jet fuel exposure coefficient from Equation (1) is -0.11, and it is statistically significant at the 5% level. The coefficient also implies economic significance of jet fuel price changes. Recall that the standard deviation of jet fuel prices shown in Figure 1 is 15.7 cents per gallon with a mean of 63.4 cents. Thus, a one standard deviation change in jet fuel price represents approximately a 25% change from the mean price. Using a 25% price change in the context of the regression results suggests a one standard deviation movement in jet fuel price results in a 2.75% change (monthly) in airline industry stock prices.